Development and validation of predictive models for skeletal malocclusion classification using airway and cephalometric landmarks

• Egile Nagusiak: Anand Marya (Egilea), Samroeng Inglam (Egilea), Nattapon Chantarapanich (Egilea), Sujin Wanchat (Egilea), Horn Rithvitou (Egilea), Prasitthichai Naronglerdrit (Egilea)
• Formatua: Liburua
• Argitaratua: BMC, 2024-09-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Abstract Objective This study aimed to develop a deep learning model to predict skeletal malocclusions with an acceptable level of accuracy using airway and cephalometric landmark values obtained from analyzing different CBCT images. Background In orthodontics, multitudinous studies have reported th...